Abstract: Improving agricultural total factor productivity (TFP) is an important way to achieve high-quality agricultural development in China. This paper constructed a spatial association network model of China’s agricultural TFP to analyze the overall characteristics, local characteristics, and individual characteristics of the network and examined the driving forces of the special correlation network of China’s agricultural TFP. Results show that 1) there are a very obvious spatial correlation and spillover effects in China’s agricultural TFP. The spatial correlation network is in a connected state. The network density shows a V-shaped fluctuating trend. In addition, the hierarchical structure is gradually broken and the network stability is gradually enhanced; 2) in the spatial network of China’s agricultural TFP, the western region belongs to the net beneficiary sector, the south and southwest regions belong to the “brokers sector”, and the Bohai Rim, Beijing-Tianjin-Hebei, and northeast regions belong to the two-way spillover sector; 3) five major provinces, including Hubei, Inner Mongolia, Henan, Shandong, and Shaanxi Province, are in the absolute core position in the spatial correlation network of China’s agricultural TFP, and they have stronger influences on the factors of agricultural production, while other provinces, including Jilin, Hainan, Qinghai, Tianjin, and Shanghai, are in an absolute marginal and passive position in the network; and 4) geographic adjacency has a positive effect on the spatial correlation of China’s agricultural TFP, and other factors such as differences in agricultural structure and differences in factor output levels have some negative effects. This paper provides a general theoretical basis and reference for understanding and improving China’s agricultural TFP.